Social Sustainability Data Observatory

Social Sustainability Data Observatory

Social Sustainability Data Observatory

Reprex

Social Sustainability Data Observatory

Sustainability is “meeting the needs of present generations without compromising the ability of future generations to meet their own needs.” Our data observatory aims to develop indicators that help companies, organizations and policymakers track that humans, now and in the future, have what they need within the limits of the ecological constraints of our world. We aim to provide high-quality KPIs, business and policy indicators to control and monitor alignment with the Social Economy Action Plan, the European Pillar of Social Rights Action Plan and Gender Equality Strategy 2020-2025 within the European Union, along with the social aspects of the 17 sustainable development goals set by the United Nations.

Download my resumé.

Interests
  • Social Economy
  • Social Rights
  • Gender Equality

Services

Automated Data Services

[Data](/services/data-curation/) [Curation](/services/data-curation/)Data sits everywhere and it is not easy to find even at home. Our curators know where to dig.
Data
Curation
Data sits everywhere and it is not easy to find even at home. Our curators know where to dig.
[Professional Data Processing](/data/open-gov/#is-there-value-left-in-open-data)Uncut diamonds need to be polished. Data is only potential information, raw and unprocessed.
Professional Data Processing
Uncut diamonds need to be polished. Data is only potential information, raw and unprocessed.
[Metadata: Documentation & Codebooks](/services/metadata/)Adding FAIR metadata exponentially increases the value of data. We use DataCite and SDMX statistical coding.
Metadata: Documentation & Codebooks
Adding FAIR metadata exponentially increases the value of data. We use DataCite and SDMX statistical coding.
[Data-as-Service](/services/data-as-service/)Reusable, easy-to-import, interoperable, always fresh data in tidy formats with a modern API.
Data-as-Service

Reusable, easy-to-import, interoperable, always fresh data in tidy formats with a modern API.
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All Data Curation Data Processing Documentation & Codebooks Data-as-Service
Metadata
Adding metadata exponentially increases the value of data. Did somebody already adjust old data to conform to constantly changing geographic boundaries? What are some practical ways of combining satellite sensory data with my organization’s records? And do I have the right to do so? Metadata logs the history of data, providing instructions on how to reuse it, also setting the terms of use. We automate this labor-intensive process applying the FAIR data concept.
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Metadata
Data Curation
We create high value key business and policy evaluation indicators. Scientific proofs require the combination of correctly matching, formatting, and verifying controlled pieces of data. Our data comes from verified and legal sources, with information about use rights and a complete history. You can always take a look at the processing code, too. We do not deal in blood diamonds.
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Data Curation
Data Processing
We create high value key business and policy evaluation indicators. Scientific proofs require the combination of correctly matching, formatting, and verifying controlled pieces of data. Our data comes from verified and legal sources, with information about use rights and a complete history. You can always take a look at the processing code, too. We do not deal in blood diamonds.
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Data Processing
Data-as-Service
We provide our clients with simple datasets, databases, harmonized survey data, and various other rich data applications; we provide them with continuous access to high-quality, re-processed, re-usable public sector and scientific data.
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Data-as-Service

Data

API to our data, our sources, how we process and validate it, how we increase its quality.

.js-id-API
Data API Metadata Surveys Open Data Data Sharing
Survey Harmonization
Ex post survey harmonization is in a way a passive form of pooling research funding because you can utilize information from surveying that were made on somebody else’s expense. The aim of ex ante survey harmonization is to maximize the value from future retrospective harmonization; in a way, it is an active form of pooling research funding, because you benefit from money spent on related open governmental and open science survey programs.
Last updated on Apr 29, 2022
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Survey Harmonization
Metadata
Uncut diamonds need to be cut, polished, and you have to make sure that they come from a legal source.
Last updated on Apr 29, 2022
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Metadata
Data Sharing
Data altruismm, sharing, and collaborative data resources.
Last updated on Apr 29, 2022
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Data Sharing
Open Data
Many countries in the world allow access to a vast array of information, such as documents under freedom of information requests, statistics, datasets. In the European Union, most taxpayer financed data in government administration, transport, or meteorology, for example, can be usually re-used. More and more scientific output is expected to be reviewable and reproducible, which implies open access.
Last updated on Apr 29, 2022
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Open Data

Skills

R

90%

Statistics

100%

Photography

10%

Contributors

data curators

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James Edwards, PhD

Curator for innovative survey data

Tile von Damm

Curator for participatory and co-creational governance

developers

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Daniel Antal

Data Scientist & Founder of the Digital Music Observatory

institutional partners

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PerGlobal

Project management, social sustainability indicators.

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Reprex

Big data for all

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rOpenGov

rOpenGov network

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Sinus-Institute

Scientific parnter, economics, statistiscs, finance

Accomplish­ments

Coursera
Neural Networks and Deep Learning
Coursera Jan 2021
See certificate
edX
Formulated informed blockchain models, hypotheses, and use cases.
See certificate
DataCamp
Object-Oriented Programming in R
DataCamp Jul 2020 – Dec 2020
See certificate

Open-Source Software

Our peer-reviewed, open source statistical software packages

We believe that transparency is the key to the highest data quality. We use only open source software. We open up the critical elements of our software for peer-review.

  • We use open-source software, there is no vendor lock-in.

  • Our data products go through many, automated (unit) tests, replacing countless error-prone human validation working hours.

  • The critical elements of our code go through external validation and peer-review by computational statisticians and data scientists.

Quickly discover relevant content by filtering our software releases..

Recent Posts

stacodelists: use standard, language-independent variable codes to help international data interoperability and machine reuse in R
A new building block of our observatories went through code peer review and was released yesterday. The statcodelists R package aim to promote the reuse and exchange of statistical information and related metadata with making the internationally standardized SDMX code lists available for the R user.
Last updated on Jul 4, 2022 3 min read
stacodelists: use standard, language-independent variable codes to help international data interoperability and machine reuse in R
What is Survey Harmonization?
Survey harmonization is a powerful research tool to increase the usability of questionnaire-based empirical research. When the same questions are asked from similarly selected German and French people, music audiences and musicians, then we can make meaningful comparisons between the public opinions of the two countries, or the different perceptions of fans and makers of music.
Last updated on May 2, 2022 3 min read
What is Survey Harmonization?
How We Add Value to Public Data With Better Curation And Documentation?
Many people ask if we can really add value to free data that can be downloaded from the Internet by anybody. We do not only work with easy-to-download data, but we know that free, public data usually requires a lot of work to become really valuable. To start with, it is not always easy to find.
Last updated on Apr 29, 2022 5 min read
How We Add Value to Public Data With Better Curation And Documentation?
How We Add Value to Public Data With Imputation and Forecasting
Public data sources are often plagued with missng values. Naively you may think that you can ignore them, but think twice: in most cases, missing data in a table is not missing information, but rather malformatted information which will destroy your beautiful visualization or stop your application from working. In this example we show how we increase the usable subset of a public dataset by 66.7%, rendering useful what would otherwise have been a deal-breaker in panel regressions or machine learning applications.
Last updated on Apr 29, 2022 7 min read
How We Add Value to Public Data With Imputation and Forecasting
The Data Sisyphus
Sisyphus was punished by being forced to roll an immense boulder up a hill only for it to roll down every time it neared the top, repeating this action for eternity. When was a file downloaded from the internet? What happened with it sense? Are their updates? Did the bibliographical reference was made for quotations? Missing values imputed? Currency translated? Who knows about it – who created a dataset, who contributed to it? Which is the final, checked, approved by a senior manager?
Last updated on Apr 29, 2022 7 min read
The Data Sisyphus
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Open-Source Software

Our peer-reviewed, open source statistical software packages

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Projects

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All Deep Learning Other
Social Sustainability Indicator Design
Create more useable, cheaper, and better-quality questionnaire-based research
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Social Sustainability Indicator Design
SurveyHarmonies
An example of using the in-built project page.
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SurveyHarmonies

Recent & Upcoming Talks

Example Talk
An example talk using Wowchemy’s Markdown slides feature.
Jun 1, 2030 1:00 PM — 3:00 PM Wowchemy HQ
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Example Talk

Recent Publications

Quickly discover relevant content by filtering publications.
Social Sustainability Data Observatory, Robert Ford (2013). An example conference paper. In ICW.

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Popular Topics

api better documentation Cultural Access and Participation curation daas data collection data curation Data integration data interoperability data processing data-altruism data-as-service data-sharing Digital Music Observatory FAIR principle metadata open-data R survey harmonization Survey recycling

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